Related papers: Loss compensation and super-resolution with excita…

Wave absorption metamaterials have been an enduring topic over the past two decades, propelled not only by novel scientific advances, but also by their extensive application potential. In this review, we aim to provide some general insights…

Multiple scattering of an electromagnetic wave as it passes through an object is a fundamental problem that limits the performance of current imaging systems. In this paper, we describe a new technique-called Series Expansion with…

We show that the powerful framework of transformation optics may be exploited for engineering the nonlocal response of artificial electromagnetic materials. Relying on the form-invariant properties of coordinate-transformed Maxwell's…

From the demonstration of saturable absorption by Vavilow and Levshin in 1926, and with invention of the laser, unavailability of strongly nonlinear materials was a key obstacle for developing optical signal processing, in particular in…

In disordered materials under mechanical stress, the produced deformation can deviate from the affine one already in the elastic regime. The nonaffine contribution was observed and characterized in numerical simulations for various systems.…

The magneto-optical effect breaks time-reversal symmetry, a unique property that makes it indispensable in nonreciprocal optics and topological photonics. Unfortunately, all natural materials have a rather weak magneto-optical response in…

Metasurfaces impart phase discontinuities on impinging electromagnetic waves that are typically limited to 0-2$\pi$. Here, we show that they can break free from this limitation and supply arbitrarily-large phase modulation over ultra-wide…

In 2011, super-resolution imaging by microsphere superlens was emerged as a simple yet effective method to overcome the diffraction limit that limits the resolution of conventional lenses. Significant progress has since been made. Key…

Improvement of label-free far-field resolution of optical imaging is possible with prior knowledge of the object such as its sparsity or accumulated by a posteriori examination of a similar class of object1-4. We show that the sole…

Due to the absence of labels and fast analyses, optical biosensors promise major advances in biomedical diagnostics, security, environmental and food safety applications. However, sensitivity of the most advanced plasmonic biosensor…

Recent experiments have revealed ultrastrong coupling between light and matter as a promising avenue for modifying material properties, such as electrical transport, chemical reaction rates, and even superconductivity. Here, we explore…

In the field of transformation optics, metamaterials mimic the effect of coordinate transformations on electromagnetic waves, creating the illusion that the waves are propagating through a virtual space. Transforming space by appropriately…

In the ELTs era, where the need for versatile and innovative solutions to produce very high spatial resolution images has become a major issue, the search of synergies with other science fields seems a logic step. One of the considered…

In this paper, we present a novel deep learning-based approach for still image super-resolution, that unlike the mainstream models does not rely solely on the input low resolution image for high quality upsampling, and takes advantage of a…

Coherent nanoscale photon sources are of paramount importance to achieving all-optical communication. Several nanolasers smaller than the diffraction limit have been theoretically proposed and experimentally demonstrated using plasmonic…

Resolution enhancements are often desired in imaging applications where high-resolution sensor arrays are difficult to obtain. Many computational imaging methods have been proposed to encode high-resolution scene information on…

As a lens capable of sending images of deep sub-wavelength objects to the far field, the hyperlens has garnered significant attention for its super-resolution and magnification capabilities. However, traditional hyperlenses require extreme…

We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can enhance the resolution of both pixel size-limited and…

Most existing super-resolution methods do not perform well in real scenarios due to lack of realistic training data and information loss of the model input. To solve the first problem, we propose a new pipeline to generate realistic…

We demonstrate a nonlinear metamaterial that can be switched between low and high transmission by controlling the power level of the incident beam. The origin of this nonlinear response is the superconducting Nb thin film employed in the…